Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, H3A 2B4, Canada.
Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom.
Neuroimage. 2022 Aug 15;257:119254. doi: 10.1016/j.neuroimage.2022.119254. Epub 2022 Apr 28.
The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure.
与年龄相关的认知衰退的个体间和个体内变异的来源仍知之甚少。我们研究了认知衰退的 20 年轨迹与老年人多模态脑结构和形态之间的关系。我们使用了 Whitehall II 研究，这是一个具有广泛特征的队列，在老年时（平均年龄为 69.52±4.9 岁）获得了 3T 脑磁共振图像，并在中年（平均年龄为 53.2±4.9 岁）和老年（平均年龄为 67.7±4.9 岁）进行了 5 次重复认知表现评估。使用非负矩阵分解，我们确定了 10 个整合皮质厚度、表面积、各向异性分数以及平均和径向扩散率的脑成分。我们观察到两个描述不同脑-认知关联的潜在变量。第一个描述了与多个认知领域的低中年表现相关的 5 个结构成分的变化，推理能力下降，但流畅性能力保持。第二个描述了与流畅性和记忆中的低中年表现相关的 6 个结构成分的变化，但保留了多种能力。潜在变量的表达预测了 3.2 年后的未来认知（平均年龄为 70.87±4.9 岁）。这种数据驱动的方法突出了脑-认知关系，其中个体在不同认知功能上的认知衰退和维持程度都与皮质结构的标志物呈正相关和负相关。
